IIoT Monitoring
IIoT Monitoring focuses on capturing, aggregating, and analyzing real-time data from industrial assets to ensure
operational visibility and predictive maintenance. Our monitoring solutions combine Linux-based edge systems,
.NET data integration layers, and modern analytics frameworks to deliver high-fidelity insights across
distributed infrastructures.
Technical Focus
- Edge Data Acquisition: Deployment of Linux gateways and sensor nodes running
Python, C++, or .NET IoT services for real-time signal capture.
- Protocols & Communication: Integration of Modbus, MQTT,
OPC UA, and HTTP REST for seamless data transmission between edge and cloud systems.
- Data Storage & Analytics: Stream ingestion and visualization using Apache Kafka,
InfluxDB, and Grafana dashboards for time-series analysis.
- .NET Integration: Implementation of data ingestion APIs and monitoring services with
ASP.NET Core and Entity Framework for enterprise data pipelines.
- Cloud & Edge Management: Deployment on Azure IoT Edge, AWS IoT Core,
and on-prem Linux nodes for hybrid monitoring architectures.
Core Competence: We build resilient, scalable monitoring frameworks that unify sensor-level data collection
with enterprise analytics — enabling predictive insights and proactive maintenance across industrial systems.
IIoT Control
IIoT Control systems enable real-time interaction with industrial devices, allowing automated and remote command execution
based on dynamic operational data. We design secure and reliable control architectures that leverage both
Linux and .NET technologies to deliver deterministic, high-performance automation.
Technical Focus
- Industrial Integration: Control of PLCs, HMIs, and embedded devices via OPC UA,
EtherCAT, and Modbus RTU/TCP under Linux-based environments.
- Real-Time Systems: Development of low-latency control applications in C++ and
C#, with RT Linux or PREEMPT_RT for time-sensitive tasks.
- Automation Frameworks: Implementation of programmable logic and process automation workflows
using .NET Core microservices and Python orchestration scripts.
- Secure Communication: End-to-end encryption and identity management via Azure IoT Hub
or MQTT TLS for safe command transmission between controllers and cloud layers.
- Human-Machine Interface (HMI): Custom-built dashboards using Blazor or
Angular + ASP.NET for interactive control and status visualization.
Core Competence: We deliver precision control platforms that seamlessly connect Linux-based edge
automation with enterprise-grade .NET orchestration — ensuring safety, responsiveness, and operational continuity.
IIoT Smart Systems
Smart Systems extend IIoT capabilities into large-scale environments such as smart cities, smart buildings, and
intelligent infrastructure. We develop interconnected systems that combine Linux-based IoT frameworks,
.NET APIs, and AI-driven analytics to create adaptive, energy-efficient, and data-aware ecosystems.
Technical Focus
- Urban & Building Sensors: Integration of environmental sensors, cameras, and actuators
communicating via LoRaWAN, NB-IoT, and 5G on Linux gateways.
- Edge & Cloud Intelligence: Local decision-making using Python AI models and
ONNX Runtime for embedded inference; cloud orchestration via Azure Digital Twins or
AWS IoT TwinMaker.
- Data Integration: Real-time data ingestion through .NET Core APIs feeding
visualization platforms such as Power BI, Grafana, or custom dashboards.
- Automation & Optimization: Dynamic control of lighting, HVAC, and traffic systems based on
AI-driven predictive algorithms and occupancy analytics.
- Security & Compliance: Implementation of secure communication, user access control, and
encrypted telemetry under Linux with OpenSSL and Azure Key Vault.
Core Competence: We architect intelligent IIoT ecosystems that transform physical environments into
responsive, data-driven systems — improving sustainability, safety, and quality of life through Linux and .NET integration.